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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Hierarchy among the crystal lattice, charge density wave, and superconducting orders in transition metal dichalcogenides

Using high-energy x-ray scattering and large-scale three-dimensional (3D) structure modeling, in this study we investigate the relationship between the crystal lattice, charge density wave (CDW), and superconducting (SC) orders in transition metal dichalcogenides (TMDs). In particular, we systematically substitute Te for Se in Ta-Se-Te solid solutions, determine changes in their crystal lattice, and relate them to changes in the CDW transition temperature, $T_{CDW}$, and SC critical temperature, $T_c$ . We find that strong lattice distortions such as buckling of Ta layers are detrimental to the CDW and SC orders. The presence of a perfect lattice order in two dimensions is a prerequisite to the emergence of CDWs but insufficient to achieve a SC ordered state. For the SC order to emerge, the Ta sublattice should also appear periodic in 3D. Local chemical disorder may promote the SC order, and the perfectness of Ta coordination polyhedra is a factor contributing to its strength. A hierarchical relationship among the crystal lattice, CDW, and SC orders thus appears to exist in TMDs in a sense that different degrees of crystal lattice order-disorder promote and maintain the CDW and SC orders to a different extent, offering an opportunity to control the latter through modifying the former by rational design. Our findings are a step towards a better understanding of the correlation between lattice and electronic degrees of freedom in TMDs. We also demonstrate an efficient experimental approach to study them in fine detail.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Positive-Sequence Modeling of Droop-Controlled Grid-Forming Inverters for Transient Stability Simulation of Transmission Systems

Here, this paper describes a positive-sequence model to represent two widely reported droop-controlled grid-forming inverters for bulk power systems simulation study. Methods of how to develop the equivalent voltage source behind impedance to represent inverters with and without inner control loops, modeling of P-f and Q-V droop controls, active and reactive power limiting modeling, and modeling of fault current limiting controls are described in detail. The model is implemented in commercially available positive-sequence simulation tools and compared with detailed electromagnetic transient models in both a single-grid-forming-inverter infinite-bus system and a modified IEEE 39-bus system. Finally, the model is tested on the full US Western Electricity Coordinating Council (WECC) system. Study results show that the model has a good level of accuracy compared to the detailed EMT models, and at the same time also achieves a high computational efficiency, which is suitable for the bulk power system simulation study.

42 ENGINEERING↗
DOE OSTI2022

Simulation of CEFR neutronic start-up tests with FENNECS

This paper presents simulation results of selected Neutronic Start-up Tests of the China Experimental Fast Reactor (CEFR) obtained by the neutronics code FENNECS that have been performed within the frame of the IAEA Coordinated Research Program I31032. The Finite Element Neutronics code FENNECS is developed at GRS and solves the few-group steady-state and transient diffusion equation using a Galerkin-based finite element approach. Its main purpose is the safety assessment of Small Modular Reactors and Micro Reactors with complex geometry (e.g., rotating control drums) which gain increased interest internationally. Serpent has been applied to create reference models of the CEFR and cross-section libraries in 10 energy groups for FENNECS. Using these libraries, the following experiments have been simulated with FENNECS: net criticality, control rod integral and differential worth, void reactivity effect, subassembly exchange reactivity effects and reaction rate distribution. The obtained satisfactory agreements with the measurements represent a valuable contribution to the validation of FENNECS. (author)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Sensor enabled data-driven predictive analytics for modeling and control with high penetration of DERs in distribution systems

The electric power grid is undergoing a tremendous transformation due to the increasing penetration of renewable energy resources beginning with wind and more recently with the distributed energy resources (DERs) such as solar and battery storage. DERs have dramatically changed the role of the distribution systems in the overall power grid, and they are expected to contribute a significant portion of power generation in the future. If current trends for DERs continue, system operation and control will need to change dramatically for improved grid reliability and resiliency. As renewable resources increase in penetration, new and challenging operational, planning, and design problems are expected to emerge. Some of the key challenges that arise in the planning and operation of the future grid are: 1) Quantifying the impact of high DER penetration in distribution systems on bulk grid behavior over multiple time scales. 2) Identifying whether a particular DER configuration/settings have a large impact on the overall grid behavior. These challenges can be addressed in an offline manner using detailed T&D grid models and they can also be addressed in an online manner using sensor measurements. In particular, the advancement and planned growth in sensor technology in power grid over various voltage levels provide us with a unique opportunity to tackle these challenges from a data analytic perspective without needing detailed T&D grid models. A few questions that naturally arise when addressing the challenges from DERs using sensor data are: 1) How can we use limited sensor measurements to monitor & control voltage stability and small signal stability of the bulk system? 2) How can we ensure that the developed data analytic methods are robust to data availability and quality issues? 3) How can we compute the developed analytics in a scalable manner using streaming measurements? In this project, we addressed the aforementioned challenges arising from DERs and answered the questions raised above on how to effectively use the sensor measurements to enhance the reliability and performance of the electric grid. Thus, the overarching goal of this project is to develop effective reduced/representative system models from data that make the computational complexity sufficiently manageable so as to be useful to simulate, analyze, and even control complex non-linear power systems dynamics with large penetrations of DERs. In order to achieve the objective, the project team established a four-fold technical approach 1) Formulated a combined transmission-distribution co-simulation framework for data generation and validation, 2) Derived reduced/representative models of power systems based on data-driven methods for efficient computation and appropriate representation of system behavior, 3) Developed data driven characterization of power system behavior based on transfer operator theory, machine learning and optimization for model estimation, 4) Incorporated a scalable data management and processing architecture using distributed Kafka streaming applications that coordinate input data streams to the developed data analytics. The key accomplishments of the project are: 1) Development of a scalable multi-timescale T&D co-simulation framework (both for steady state and for dynamic co-simulation) using commercial solvers (PSSE and GridLAB-D). The steady-state T&D co-simulation interface is shared with our industry partner (PJM). 2) A structured reduced order dynamic model of distribution systems that can represent partial motor stalling along with a systematic procedure to derive the model parameters. 3) A PMU based online method to monitor, localize and mitigate fault-induced delayed voltage recovery using DER reactive support and load control in distribution systems. 4) Development of linear operator based robust methodologies for dynamic state estimation, uncertainty quantification, system identification and trajectory prediction for power system dynamics. 5) An adaptive damping control for utilizing wind energy resources to provide oscillation damping and system stability. 6) Implementation of Kafka-based framework for efficient processing of streaming data using Linux-based local virtual environment.

DER integration↗
DOE OSTI2024

Infrastructure-Based Cooperative Perception at a Traffic Intersection: Overview and Challenges: Preprint

Recent advancement in autonomous driving vehicles and V2X communication has attracted increasing attention towards Intelligent Transportation Systems to build a safe and reliable traffic intersection. However, most of the systems are still at the initial stages and require significant progress to become a reality. This paper presents an overview of NREL Infrastructure Perception and Control (IPC) framework which is an open-source track-data fusion engine which takes input from infrastructure-based perception sensors and cooperatively shared messages from Connected Autonomous Vehicles (CAVs) and Connected Vehicle (CVs) and the challenges associated with deploying such cooperative perception framework at a four-way traffic intersection in the city of Colorado Springs, CO, USA. The sensor data is collected by deploying two radars and two LiDAR sensors on the IPC mobile lab and two radars on diagonally opposite traffic poles at the proposed intersection. The sensor output results imply the need for rapid sensor calibration to bring the collective perception to a common coordinate frame, the importance of time synchronization between the sensors in order to capture accurate spatial and temporal alignment of the objects, and the need for a health monitoring system with fail safe closed-loop detection model for real-time deployment.

camera↗
DOE OSTI2021

Structural Manipulation of a Zirconocene-Based Porous Coordination Cage Using External and Host–Guest Stimuli

Porous coordination cages (PCCs) constructed from a zirconocene-based cluster have drawn great attention for their high stability and structural tunability. These features have enabled these cages to be utilized for a wide array of applications. Here this work demonstrates the structural flexibility and stimulus-responsive features of two interconvertible zirconocene-based PCCs. The subjects, PCC-20c (capsular) and PCC-20t (tetrahedral), are constructed from the same cluster and ligand but exhibit different shapes and properties. In the synthetic study of the cages, it is found that higher temperatures of synthesis yield PCC-20c in several different crystalline phases while lower temperatures of synthesis yield pure phase PCC-20t. Thermodynamic studies on the interconversion of the two cages show that the conversion from PCC-20t into PCC-20c is an entropically driven process and can be largely affected by the solvent environment. Additionally, the process of PCC-20t/c conversion can be mediated by the counter anions and light irradiation as evidenced by the change in equilibrium constants under these influences. The current studies are conducted to decipher how the PCC-20t/c phase can be controllably synthesized, interconverted, and their properties can be modified under the use of external stimuli: heat, light, and guest molecules.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Deep Understanding of Strong Metal Interface Confinement: A Journey of Pd/FeO x Catalysts

Tuning the atomic interface configuration of noble metals (NMs) and transition-metal oxides is an effective straightforward yet challenging strategy to modulate the activity and stability of heterogeneous catalysts. Herein, Pd supported on mesoporous Fe 2 O 3 with a high specific surface area was rationally designed and chosen to construct the Pd/iron oxide interface. As a versatile model, the physicochemical environments of Pd nanoparticles (NPs) could be precisely controlled by taming the reduction temperature. The experimental and density functional theory calculation results unveiled that the catalyst in the support–metal interface confinement (SMIC) state showed significantly enhanced catalytic activity and sintering resistance for CO oxidation. The constructed Fe sites at the interfaces between FeO x overlayers and Pd NPs not only provided additional coordinative unsaturated ferrous sites for the adsorption and activation of O 2 , thereby facilitating the activation efficiency of O 2 , but also impressively changed the reaction pathway of CO oxidation. As a result, the catalyst followed the Pd/Fe dual-site mechanism instead of the classical Mars–van Krevelen mechanism. For the catalyst in the strong metal–support interaction (SMSI) state, its catalytic activity was seriously suppressed because of the excessive encapsulation of the active Pd sites by FeO x overlayers. Thus, the present study therefore provides detailed insights into the SMIC and SMSI in ferric oxide-supported Pd catalysts, which could guide the preparation of highly efficient supported catalysts for practical applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A Nanocrystal Catalyst Incorporating a Surface Bound Transition Metal to Induce Photocatalytic Sequential Electron Transfer Events

Heterogeneous photocatalysis is less common but can provide unique avenues for inducing novel chemical transformations and can also be utilized for energy transductions, i.e., the energy in the photons can be captured in chemical bonds. Here, we developed a novel heterogeneous photocatalytic system that employs a lead-halide perovskite nanocrystal (NC) to capture photons and direct photogenerated holes to a surface bound transition metal Cu-site, resulting in a N–N heterocyclization reaction. The reaction starts from surface coordinated diamine substrates and requires two subsequent photo-oxidation events per reaction cycle. We establish a photocatalytic pathway that incorporates sequential inner sphere electron transfer events, photons absorbed by the NC generate holes that are sequentially funneled to the Cu-surface site to perform the reaction. The photocatalyst is readily prepared via a controlled cation-exchange reaction and provides new opportunities in photodriven heterogeneous catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Advanced supramolecular design for direct ink writing of soft materials

The exciting advancements in 3D-printing of soft materials are changing the landscape of materials development and fabrication. Among various 3D-printers that are designed for soft materials fabrication, the direct ink writing (DIW) system is particularly attractive for chemists and materials scientists due to the mild fabrication conditions, compatibility with a wide range of organic and inorganic materials, and the ease of multi-materials 3D-printing. Inks for DIW need to possess suitable viscoelastic properties to allow for smooth extrusion and be self-supportive after printing, but molecularly facilitating 3D printability to functional materials remains nontrivial. While supramolecular binding motifs have been increasingly used for 3D-printing, these inks are largely optimized empirically for DIW. Hence, this review aims to establish a clear connection between the molecular understanding of the supramolecularly bound motifs and their viscoelastic properties at bulk. Herein, extrudable (but not self-supportive) and 3D-printable (self-supportive) polymeric materials that utilize noncovalent interactions, including hydrogen bonding, host–guest inclusion, metal–ligand coordination, micro-crystallization, and van der Waals interaction, have been discussed in detail. In particular, the rheological distinctions between extrudable and 3D-printable inks have been discussed from a supramolecular design perspective. Examples shown in this review also highlight the exciting macroscale functions amplified from the molecular design. Challenges associated with the hierarchical control and characterization of supramolecularly designed DIW inks are also outlined. The perspective of utilizing supramolecular binding motifs in soft materials DIW printing has been discussed. Finally, this review serves to connect researchers across disciplines to develop innovative solutions that connect top-down 3D-printing and bottom-up supramolecular design to accelerate the development of 3D-print soft materials for a sustainable future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Geometrical frustration and competing orders in the dipolar trimerized triangular lattice

Here, we introduce and explore low-energy configurations in two-dimensional arrays consisting of Ising-type dipolar coupled nanomagnets lithographically defined onto three-nanomagnet vertices arranged in a triangular coordination. Thus, the system is dubbed the trimerized triangular lattice. Employing synchrotron-based photoemission electron microscopy, we perform temperature-dependent magnetic imaging of moment configurations. These states are then characterized in terms of spin correlations and magnetic structure factors. The results reveal a competition between ferromagnetic and vortex dominated orders, which can be controlled by varying the relevant lattice parameter and the corresponding competing interactions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Uranium and Nickel Partitioning in a Contaminated Riparian Wetland

Uranium (U) and nickel (Ni) released 50 years ago have been immobilized in the Tims Branch wetlands located on the Savannah River Site in the United States. Sediments were collected from seven locations to identify the factors responsible for this attenuation. Ni and U contents in the solids were significantly correlated, suggesting that depositional as opposed to chemical processes contributed to their spatial distribution. Based on sequential extractions, 63 ± 16% of the U was partitioned into the organic fraction, whereas Ni was distributed between several sediment fractions. An inverse pH-organic matter (OM) correlation and positive correlations of OM with total U and organic-bound U/Ni suggest that increased OM preservation and binding to the mineral surfaces were likely responsible for Ni- and especially U-sediment retention (Tims Branch pH = 4.84 ± 0.68). EXAFS analysis indicated the predominance of U(VI) coordinated with clay minerals (~65%), together with ~35% coordinated to either OM (in areas with elevated OM levels) or iron oxides. The desorption-Kd coefficients of U (3972 ± 1370 L/kg) and Ni (30 ± 8 L/kg) indicate that dissolved Ni poses a greater long-term risk than dissolved U for migrating downstream. This study suggests that a delicate balance of geochemical properties controls whether wetlands behave as sinks or sources of contaminants.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2022

Designing the PR100 Study: Puerto Rico Grid Resilience and Transition to 100% Renewable Energy

Puerto Rico has committed to meeting its electricity needs with 100% renewable energy by 2050, along with realizing interim goals of 40% by 2025, 60% by 2040, the phaseout of coal-fired generation by 2028, and a 30% improvement in energy efficiency by 2040 as established in Act 17. [1] To meet these goals and support widespread end-use electrification, the territory must explore how renewable energy and other generation technologies can be developed with energy storage, distributed generation, distribution control, electric vehicles, and energy efficient and responsive loads in each of Puerto Rico's cities and communities. To support Puerto Rico in reaching its renewable energy goals; help ensure energy system resilience against future extreme weather events; improve energy justice; and provide inputs to LUMA Energy's walk, jog, and run approach in its coordinated planning roadmap, the U.S. Department of Energy, National Renewable Energy Laboratory, Argonne National Laboratory, Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, Pacific Northwest National Laboratory and Sandia National Laboratories propose to evaluate 100% renewable energy pathways through an integrated analysis process. This talk will present steps in designing a two-year study entitled Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy (PR100). [1] U.S. Energy Information Administration (EIA). 2020. Puerto Rico Territory Energy Profile.

100% renewable energy↗
DOE OSTI2021

Control of Catalyst Isomers Using an N -Phenyl-Substituted RN(CH 2 CH 2 P i Pr 2 ) 2 Pincer Ligand in CO 2 Hydrogenation and Formic Acid Dehydrogenation

A novel pincer ligand, i Pr PN Ph P [PhN- (CH 2 CH 2 P i Pr 2 ) 2 ], which is an analogue of the versatile MACHO ligand, iPr PN H P [HN(CH 2 CH 2 P i Pr 2 ) 2 ], was synthesized and characterized. The ligand was coordinated to ruthenium, and a series of hydride-containing complexes were isolated and characterized by NMR and IR spectroscopies, as well as X-ray diffraction. Comparisons to previously published analogues ligated by iPr PN H P and iPr PN Me P [CH 3 N(CH 2 CH 2 P i Pr 2 ) 2 ] illustrate that there are large changes in the coordination chemistry that occur when the nitrogen substituent of the pincer ligand is altered. For example, ruthenium hydrides supported by the iPr PN Ph P ligand always form the syn isomer (where syn/anti refer to the relative orientation of the group on nitrogen and the hydride ligand on ruthenium), whereas complexes supported by iPr PN H P form the anti isomer and complexes supported by iPr PN Me P form a mixture of syn and anti isomers. We evaluated the impact of the nitrogen substituent of the pincer ligand in catalysis by comparing a series of iPr PN R P (R = H, Me, Ph)-ligated ruthenium hydride complexes as catalysts for formic acid dehydrogenation and carbon dioxide (CO 2 ) hydrogenation to formate. The iPr PN Ph P-ligated species is the most active for formic acid dehydrogenation, and mechanistic studies suggest that this is likely because there are kinetic advantages for catalysts that operate via the syn isomer. In CO 2 hydrogenation, the iPr PN Ph P-ligated species is again the most active under our optimal conditions, and we report some of the highest turnover frequencies for homogeneous catalysts. Experimental and theoretical insights into the turnover-limiting step of catalysis provide a basis for the observed trends in catalytic activity. Additionally, the stability of our complexes enabled us to detect a previously unobserved autocatalytic effect involving the base that is added to drive the reaction. Overall, by modifying the nitrogen substituent on the MACHO ligand, we have developed highly active catalysts for formic acid dehydrogenation and CO 2 hydrogenation and also provided a framework for future catalyst development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Sequential Separation of Linear, Mono–, and Di–Branched Hexane Isomers on a Robust Coordination Polymer with Nonbonding Flexibility

Efficient separation of hexane isomers is a crucial process for upgrading gasoline. Herein, the sequential separation of linear, mono-, and di-branched hexane isomers by a robust stacked 1D coordination polymer termed as Mn-dhbq ([Mn(dhbq)(H 2 O) 2 ], H 2 dhbq = 2,5-dihydroxy-1,4-benzoquinone) is reported. The interchain space of the activated polymer is of optimal aperture size (5.58 Å) that could exclude 2,3-dimethylbutane, while the chain structure can discriminate n-hexane with high capacity (1.53 mmol g –1 at 393 K, 6.67 kPa) by high-density open metal sites (5.18 mmol g –1 ). With the temperature- and adsorbate-dependent swelling of interchain spaces, the affinity between 3-methylpentane and Mn-dhbq can be deliberately controlled from sorption to exclusion, and thus a complete separation of ternary mixture can be achieved. Column breakthrough experiments confirm the excellent separation performance of Mn-dhbq. Furthermore, the ultrahigh stability and easy scalability further highlight the application prospect of Mn-dhbq for separation of hexane isomers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Applications of Multibody for Everybody (M4E) in Marine Energy

Multibody for Everybody (M4E) is an open-source symbolic dynamics modeling framework designed to automate the derivation of equations of motion and simulation of constrained multibody systems using the joint coordinate formulation.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Diversity-oriented synthesis of polymer membranes with ion solvation cages

Microporous polymers feature shape-persistent free volume elements (FVEs), which are permeated by small molecules and ions when used as membranes for chemical separations, water purification, fuel cells, and batteries. It remains a significant challenge to identify FVEs with analyte specificity, due to difficulties in generating microporous polymer libraries with sufficient diversity for screening their properties. Here, we describe a diversity-oriented synthetic (DOS) strategy for microporous polymer membranes from which we identified those whose FVEs serve as solid solvation cages for lithium ions (Li + ). Furthermore, key elements of our strategy included diversification of bis(catechol)-type monomers via multi-component Mannich reactions to introduce Li+-coordinating functionality within individual FVEs, topology-enforcing polymerizations for generating macromolecular skeletal diversity for networking FVEs into different pore architectures, and several classes of on-polymer reactions for diversifying pore geometries and dielectric properties. Lead candidate polymer membranes featuring explicit ion solvation cages exhibited both higher ionic conductivity and higher cation transference number than control membranes where FVEs were aspecific, which indicates conventional bounds for membrane permeability and selectivity for ion transport can be overcome.4 These advantages are tied to enhanced Li + partitioning from the electrolyte when the cages are present, higher diffusion barriers for anions within the pores, and network-enforced restrictions on the number of solvent molecules bound to Li+ by comparison to the bulk electrolyte, which reduces the effective mass of the working ion. Such membranes show promise as anode-stabilizing interlayers in high-voltage lithium-metal batteries for electric mobility.

42 ENGINEERING↗
DOE OSTI2025

Tailoring multi-dimensional hierarchical self-assembly of metallacages through balancing non-covalent interactions

Despite advances in non-covalent interactions and complex self-assembly, precise control of multi-dimensional hierarchical self-assembly (HSA) from the molecular level to larger scales remains challenging. Herein, we designed and synthesized two rigid tetratopic ligands with multiple preset driving forces, and assembled them with Zn(II) ions to obtain metallacages SC6 and SC12 . Through balancing multiple non-covalent interactions, including metal–organic coordination, hydrophobic, and π–π interactions, SC6 can hierarchically self-assemble driven by a poor solvent, from one-dimensional nanowires to super-helical nanostructures via non-equilibrium self-assembly, progressing continuously with time and the increasing proportion of the poor solvent. However, for SC12 with enhanced hydrophobic interactions, two-dimensional monolayer nanogrids were formed by hierarchical self-assembly. Notably, these structures can be recycled back to primary metallacages through simple dissolution, highlighting their potential for efficient recycling and reuse. These results demonstrate that multi-dimensional hierarchical structures enable precise construction by balancing non-covalent interactions through a bottom-up self-assembly approach. This study provides deeper insight into the mechanisms of HSA and a promising strategy for the tailored creation of complex structures and sustainable porous materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Coordinated Steering Angle and Yaw Moment Distribution to Increase Vehicle Regenerative Energy in Autonomous Driving

This paper presents an algorithm that increases vehicle regenerative braking energy recovery in autonomous driving by leveraging connected and automated vehicle (CAV) technology. Autonomous vehicles may select different maneuvers to increase kinetic energy recovery during deceleration. In the proposed algorithm, the cornering resistance that influences regenerative energy and energy consumption is defined in terms of steering angle during regenerative braking. In particular, a model predictive controller that distributes control inputs of the vehicle is adopted to reduce the cornering resistance for increasing regenerative braking torque. Utilizing the information from CAV technology, this algorithm enables the vehicle to safely conduct braking while increasing its regenerative energy recovery. CarSim-Simulink joint simulations demonstrate the effectiveness of the proposed method.

Choi, Junghyun↗